Practical design and performance of physical reservoir computing using hysteresis
Yuhei Yamada

TL;DR
This paper explores the design and performance of a practical physical reservoir computing system based on hysteresis, providing guidelines for implementation and analyzing its limitations.
Contribution
It introduces a simple, experimentally feasible hysteresis-based reservoir design and evaluates its performance for practical physical reservoir computing applications.
Findings
Effective reservoir design using hysteretic systems
Performance analysis and limitations identified
Guidelines for practical implementation provided
Abstract
Physical reservoir computing is an innovative idea for using physical phenomena as computational resources. Recent research has revealed that information processing techniques can improve the performance, but for practical applications, it is equally important to study the level of performance with a simple design that is easy to construct experimentally. We focus on a reservoir composed of independent hysteretic systems as a model suitable for the practical implementation of physical reservoir computing. In this paper, we discuss the appropriate design of this reservoir, its performance, and its limitations. This research will serve as a practical guideline for constructing hysteresis-based reservoirs.
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Taxonomy
TopicsNeural Networks and Reservoir Computing · Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices
MethodsFocus
